A* (A Star) Search Algorithm - Computerphile
🛈⏬Improving on Dijkstra, A* takes into account the direction of your goal. Dr Mike Pound explains. Correction: At 8min 38secs 'D' should, of course, be 14 not 12. This does not change the result. Dijkstra's Algorithm: https://youtu.be/GazC3A4OQTE How GPS Works: https://youtu.be/EUrU1y5is3Y http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comTimes Tables, Mandelbrot and the Heart of Mathematics
🛈⏬The good old times tables lead a very exciting secret life involving the infamous Mandelbrot set, the ubiquitous cardioid and a myriad of hidden beautiful patterns. Time for the Mathologer to go on a serious fact-finding mission. For those of you who’d like to play around a bit with the stunning times table diagrams that we discuss in this video, download the .cdf file http://www.qedcat.com/cardioid.cdf and open it with the free cdf player which you can download from Wolfram Research (the people behind Wolfram Alpha and Mathematica). If you have access to Mathematica you can also open my .cdf file in Mathematica and play with the code. For those of you who are looking for a bit of a challenge, ponder this: 1) Starting with the fact that the nephroid arises from parallel rays being reflected inside a cylindrical coffee cup, try to convince yourself that the 3 times table really does produce the nephroid (some really neat geometry at work here, very similar to the argument for the cardioid that I talk about at the end of the video). (Added 8 November 2015 check out the proof at http://www.qedcat.com/nephroid_proof.pdf ) 2) Why do the diagrams for all the times tables have a horizontal mirror symmetry? 3) Try to explain the pretty patterns corresponding to the 51 and 99 times tables modulo 200 that I display in the video (around the 9:30 mark). 4) (For those of you with a very strong math background) Try to figure out why the cardioid shows up in the Mandelbrot set. The discovery of the stunning patterns that I discuss in this video is due to the mathematician Simon Plouffe. Check out this article http://tinyurl.com/o2hbtsa and his website http://plouffe.fr for other stunning visualisations using modular arithmetic. Quite a few animations have been contributed by various people and linked to in the comments: Here is one of the nicest ones by Mathias Lengler: https://mathiaslengler.github.io/TimesTableWebGL/ Enjoy! Burkard Polster and Giuseppe Geracitano P.S.: The music we are playing at the end is called Shoulder Closure by Gunnar Olsen. It's part of the free YouTube music library. A really nice piece , isn't it?David Letterman Mathematics Genius Prodigy Daniel Tammet Math 3.14 Pi Day
🛈⏬Math has been rebuilt from zero. Download the free slides presented in India from https://t.co/KtMKbkMCD8 David Letterman Mathematics Prodigy Genius Daniel Tammet Math 3.14 Pi DayDimensionality Reduction - The Math of Intelligence #5
🛈⏬Most of the datasets you'll find will have more than 3 dimensions. How are you supposed to understand visualize n-dimensional data? Enter dimensionality reduction techniques. We'll go over the the math behind the most popular such technique called Principal Component Analysis. Code for this video: https://github.com/llSourcell/Dimensionality_Reduction Ong's Winning Code: https://github.com/jrios6/Math-of-Intelligence/tree/master/4-Self-Organizing-Maps Hammad's Runner up Code: https://github.com/hammadshaikhha/Math-of-Machine-Learning-Course-by-Siraj/tree/master/Self%20Organizing%20Maps%20for%20Data%20Visualization Please Subscribe! And like. And comment. That's what keeps me going. I used a screengrab from 3blue1brown's awesome videos: https://www.youtube.com/channel/UCYO_jab_esuFRV4b17AJtAw More learning resources: https://plot.ly/ipython-notebooks/principal-component-analysis/ https://www.youtube.com/watch?v=lrHboFMio7g https://www.dezyre.com/data-science-in-python-tutorial/principal-component-analysis-tutorial https://georgemdallas.wordpress.com/2013/10/30/principal-component-analysis-4-dummies-eigenvectors-eigenvalues-and-dimension-reduction/ http://setosa.io/ev/principal-component-analysis/ http://sebastianraschka.com/Articles/2015_pca_in_3_steps.html https://algobeans.com/2016/06/15/principal-component-analysis-tutorial/ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5wScience Confirms the Bible
🛈⏬Learn about DNA as evidence for the infinite God, the basics of genetics and natural selection as they relate to biblical “kinds,” the origin of so-called races, the truth about Cain's wife, evidence for the worldwide Flood, the actual time of the Ice Age, literal vs. figurative creation days, the origin of death, dating methods, and more. The Bible is true. Science confirms it, and with the help of this video, you and your teens will be better equipped to defend it! GET MORE ANSWERS: http://www.AnswersInGenesis.org RESOURCES: Science Confirms The Bible (Ken Ham Speaks to Teens) featuring Ken Ham: http://bit.ly/2MOwZ7c The Great Debate on Science and the Bible - Young Earth vs. Old Earth featuring Ken Ham, Dr. Walt Kaiser, Dr. Jason Lisle, and Dr. Hugh Ross: http://bit.ly/2IXsZ1M The Evolution of Darwin: His Science featuring Dr. David Menton: http://bit.ly/2u8grQ2 Science 101 pack featuring Wes Olson: http://bit.ly/2tWwEZcWHY STUDY MATHEMATICS - Vortex Math part 1 and 2
🛈⏬Follow me here ► https://steemit.com/@digitaltrends47 Mathematics or numbers is the cradle of all creations. Without this the world cannot move even an inch. Every human being, like nurse or a farmer, a carpenter , a mechanic, a shopkeeper or a doctor, an engineer or a scientist, a musician or a magician, electrician or a fisherman , a cook or a driver , everyone needs mathematics in their day-to-day life. Even animal , plants, and insects, has the Golden ratio , the geometrical pattern , they use mathematics in their everyday life for existence. But did you know , that you can find the secret of the universe by just using mathematics? Music by AndewG - https://soundcloud.com/andrew_g-2 To use this music in your videos or media projects, you must first purchase a license. Life could be a dream by Future James - https://soundcloud.com/futurejames KEYWORDS: why study math, why study math in high school, why study maths, why study maths at a level, why study pure math, why we study math why study mathematics the importance of math vortex based math intro to vortex math, randy powell vortex math, vortex based math, vortex math, vortex math 3 6 9, vortex math animation, vortex math application, vortex math chart, vortex math circle, vortex math coil, vortex math debunked, vortex math definition, vortex math diagram, vortex math explained, vortex math fibonacci, vortex math flower of life, vortex math free energy, vortex math marko rodin, vortex math music, vortex math nikola tesla, vortex math number 9, vortex math randy, vortex math randy powell, vortex math rodin, vortex math ted, vortex math ted talk, vortex math tesla, vortex math video, vortex math wiki, vortex math youtube, vortex mathematics, vortex mathematics debunked, vortex mathmatics, vortex maths, what is vortex mathSearch A Maze For Any Path - Depth First Search Fundamentals (Similar To -The Maze- on Leetcode)
🛈⏬Come Visit Us: https://backtobackswe.com Question: Given a 2D array of black and white entries representing a maze with designated entrance and exit points, find a path from the entrance to the exit, if one exists. The code: https://github.com/bephrem1/backtobackswe/blob/master/Graphs/searchAMaze.java Graph search methodologies apply well to problems that have an aspect of a spatial relationship. Approach 1 (Brute Force) We could try to enumerate all possible paths in the maze from the start to the finish and then check all paths to see if any of them are valid (have all white squares, aka do not run over a wall). This is both naive and extremely costly in terms of time. Approach 2 (Graph BFS or DFS) We will imagine each cell as a vertex and each adjacent relationship as the edges connecting nodes. Do we use DFS or BFS? If we use BFS we know that the path that we find will be the shortest path because of how it searches (wide, going out layer by layer). If we use DFS we can have the call stack remember the path making things easier to implement. If we hit the end cell, then we will know that every call below in the call stack has a node apart of the answer path. Since the problem just wants any path then we will use DFS since it is more straight-forward. Complexities Time: O( | V | + | E | ) The standard time complexity for DFS Space: O( | V | ) We will at maximum the length of the path on the call stack through our recursion Note: The problem on Leetcode requires BFS to pass because DFS will not always find the shortest path, but I did DFS in this video just for teaching purposes. ++++++++++++++++++++++++++++++++++++++++++++++++++ HackerRank: https://www.youtube.com/channel/UCOf7UPMHBjAavgD0Qw5q5ww Tuschar Roy: https://www.youtube.com/user/tusharroy2525 GeeksForGeeks: https://www.youtube.com/channel/UC0RhatS1pyxInC00YKjjBqQ Jarvis Johnson: https://www.youtube.com/user/VSympathyV Success In Tech: https://www.youtube.com/channel/UC-vYrOAmtrx9sBzJAf3x_xw ++++++++++++++++++++++++++++++++++++++++++++++++++ This question on Leetcode: https://leetcode.com/articles/the-maze/ This question is number 19.1 in Elements of Programming Interviews by Adnan Aziz, Tsung-Hsien Lee, and Amit Prakash.A* Pathfinding Tutorial
🛈⏬In this tutorial I teach the basics of how the astar pathfinding algorithm works. The introduction effect is a free template from Bus Productions. http://www.youtube.com/watch?v=Co-CuKfnxEw&feature=related The introduction sound clip (SFX Bible ss03612) was downloaded from soundsnap.com and used under their royalty free license.Step by Step: Alpha Beta Pruning
🛈⏬CS188 Artificial Intelligence UC Berkeley, Spring 2013 Instructor: Prof. Pieter Abbeel5. Search: Optimal, Branch and Bound, A*
🛈⏬MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Patrick Winston This lecture covers strategies for finding the shortest path. We discuss branch and bound, which can be refined by using an extended list or an admissible heuristic, or both (known as A*). We end with an example where the heuristic must be consistent. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.eduData Structures: Hash Tables
🛈⏬Learn the basics of Hash Tables, one of the most useful data structures for solving interview questions. This video is a part of HackerRank's Cracking The Coding Interview Tutorial with Gayle Laakmann McDowell. http://www.hackerrank.com/domains/tutorials/cracking-the-coding-interview?utm_source=video&utm_medium=youtube&utm_campaign=ctciD-Separation
🛈⏬Prof. Abbeel steps through the execution of d-separation for a few example Bayes' nets.The Map of Mathematics
🛈⏬The entire field of mathematics summarised in a single map! This shows how pure mathematics and applied mathematics relate to each other and all of the sub-topics they are made from. If you would like to buy a poster of this map, they are available here: http://www.redbubble.com/people/dominicwalliman/works/25095968-the-map-of-mathematics I have also made a version available for educational use which you can find here: https://www.flickr.com/photos/95869671@N08/32264483720/in/dateposted-public/ To err is to human, and I human a lot. I always try my best to be as correct as possible, but unfortunately I make mistakes. This is the errata where I correct my silly mistakes. My goal is to one day do a video with no errors! 1. The number one is not a prime number. The definition of a prime number is a number can be divided evenly only by 1, or itself. And it must be a whole number GREATER than 1. (This last bit is the bit I forgot). 2. In the trigonometry section I drew cos(theta) = opposite / adjacent. This is the kind of thing you learn in high school and guess what. I got it wrong! Dummy. It should be cos(theta) = adjacent / hypotenuse. 3. My drawing of dice is slightly wrong. Most dice have their opposite sides adding up to 7, so when I drew 3 and 4 next to each other that is incorrect. 4. I said that the Gödel Incompleteness Theorems implied that mathematics is made up by humans, but that is wrong, just ignore that statement. I have learned more about it now, here is a good video explaining it: https://youtu.be/O4ndIDcDSGc 5. In the animation about imaginary numbers I drew the real axis as vertical and the imaginary axis as horizontal which is opposite to the conventional way it is done. Thanks so much to my supporters on Patreon. I hope to make money from my videos one day, but I’m not there yet! If you enjoy my videos and would like to help me make more this is the best way and I appreciate it very much. https://www.patreon.com/domainofscience Here are links to some of the sources I used in this video. Links: Summary of mathematics: https://en.wikipedia.org/wiki/Mathematics Earliest human counting: http://mathtimeline.weebly.com/early-human-counting-tools.html First use of zero: https://en.wikipedia.org/wiki/0#History http://www.livescience.com/27853-who-invented-zero.html First use of negative numbers: https://www.quora.com/Who-is-the-inventor-of-negative-numbers Renaissance science: https://en.wikipedia.org/wiki/History_of_science_in_the_Renaissance History of complex numbers: http://rossroessler.tripod.com/ https://en.wikipedia.org/wiki/Mathematics Proof that pi is irrational: https://www.quora.com/How-do-you-prove-that-pi-is-an-irrational-number and https://en.wikipedia.org/wiki/Proof_that_%CF%80_is_irrational#Laczkovich.27s_proof Also, if you enjoyed this video, you will probably like my science books, available in all good books shops around the work and is printed in 16 languages. Links are below or just search for Professor Astro Cat. They are fun children's books aimed at the age range 7-12. But they are also a hit with adults who want good explanations of science. The books have won awards and the app won a Webby. Frontiers of Space: http://nobrow.net/shop/professor-astro-cats-frontiers-of-space/ Atomic Adventure: http://nobrow.net/shop/professor-astro-cats-atomic-adventure/ Intergalactic Activity Book: http://nobrow.net/shop/professor-astro-cats-intergalactic-activity-book/ Solar System App: http://www.minilabstudios.com/apps/professor-astro-cats-solar-system/ Find me on twitter, instagram, and my website: http://dominicwalliman.com https://twitter.com/DominicWalliman https://www.instagram.com/dominicwalliman https://www.facebook.com/dominicwallimanMaze Solving - Computerphile
🛈⏬Putting search algorithms into practice. Dr Mike Pound reveals he likes nothing more in his spare time, than sitting in front of the TV coding. EXTRA BITS: https://youtu.be/kF7KlThoT9w Mike's Code: http://bit.ly/MikesMarvellousMazes http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comUniform Cost Search
A* Search
Leonard Susskind - Why does mathematics work? - Differential Equations in Action
🛈⏬This video is part of an online course, Differential Equations in Action. Check out the course here: https://www.udacity.com/course/cs222.A* Pathfinding Tutorial
🛈⏬____PLEASE READ_____ I made a flaw in the explanation of the logic. In step 3 (Pick block with lowest F), I infered that the block must be adjacent to the current block, however the lowest F is picked from all blocks that have been processed but that have not yet been closed. Thus the backtracking I did at 9:40 isn't necessary since your evaluating the same list of Fs no matter what your current node is. If I had done this correctly I would have ended up checking several more nodes. At 12:28 I ended up selecting a node with a F of 68 however there were several options with a F of 60 that I should have chosen. ______________________ In this video I'll be showing you how A* Path Finding algorithms work. This is very useful when programming AI in games. Here's the link to the tutorial I mentioned http://www.policyalmanac.org/games/aStarTutorial.htmGraph Traversals - Breadth First and Depth First
🛈⏬Clear explanation of Breadth First (BFS) and Depth First (DFS) graph traversals Modified from : http://www.youtube.com/watch?v=zLZhSSXAwxIRecursion, the Fibonacci Sequence and Memoization || Python Tutorial || Learn Python Programming
🛈⏬Let’s explore recursion by writing a function to generate the terms of the Fibonacci sequence. We will use a technique called “memoization” to make the function fast. We’ll first implement our own caching, but then we will use Python’s builtin memoization tool: the lru_cache decorator. ➢➢➢➢➢➢➢➢➢➢ To learn Python, you can watch our playlist from the beginning: https://www.youtube.com/watch?v=bY6m6_IIN94&list=PLi01XoE8jYohWFPpC17Z-wWhPOSuh8Er- ➢➢➢➢➢➢➢➢➢➢ We recommend: Python Cookbook, Third edition from O’Reilly http://amzn.to/2sCNYlZ The Mythical Man Month - Essays on Software Engineering & Project Management http://amzn.to/2tYdNeP Shop Amazon Used Textbooks - Save up to 90% http://amzn.to/2pllk4B ➢➢➢➢➢➢➢➢➢➢ Subscribe to Socratica: http://bit.ly/1ixuu9W To support more videos from Socratica, visit Socratica Patreon https://www.patreon.com/socratica Socratica Paypal https://www.paypal.me/socratica We also accept Bitcoin! :) Our address is: 1EttYyGwJmpy9bLY2UcmEqMJuBfaZ1HdG9 ➢➢➢➢➢➢➢➢➢➢ Python instructor: Ulka Simone Mohanty Written & Produced by Michael Harrison FX by Andriy KostyukMathematics: Beauty vs Utility - Numberphile
🛈⏬Should mathematics be done for its pure beauty or should it have practical uses? And why are many mathematicians so bad at outreach? Discussion with famous French mathematician, Cédric Villani. More Villani videos: http://bit.ly/Villani_Videos Numberphile videos on Magic Squares: http://bit.ly/MagicSquareVideos Cédric Villani website: http://cedricvillani.org His book Birth of a Theorem (Amazon): http://bit.ly/BirthOfATheorem Numberphile is supported by the Mathematical Sciences Research Institute (MSRI): http://bit.ly/MSRINumberphile We are also supported by Science Sandbox, a Simons Foundation initiative dedicated to engaging everyone with the process of science. NUMBERPHILE Website: http://www.numberphile.com/ Numberphile on Facebook: http://www.facebook.com/numberphile Numberphile tweets: https://twitter.com/numberphile Subscribe: http://bit.ly/Numberphile_Sub Videos by Brady Haran Patreon: http://www.patreon.com/numberphile Brady's videos subreddit: http://www.reddit.com/r/BradyHaran/ Brady's latest videos across all channels: http://www.bradyharanblog.com/ Sign up for (occasional) emails: http://eepurl.com/YdjL9Heuristic Search - Hill Climbing
🛈⏬Reference : AI- A Modern Approach by Russel Norvig Answer to query on no. of attacks in the 8-queens problem: Here you have 5 horizontal attacks (4 direct ones and 1 indirect). 8 direct horizontal attacks and 4 indirect horizontal attacks. That makes it 17 attacks. You can pause the video and map those attacks.Machine Learning - Supervised VS Unsupervised Learning
🛈⏬Enroll in the course for free at: https://bigdatauniversity.com/courses/machine-learning-with-python/ Machine Learning can be an incredibly beneficial tool to uncover hidden insights and predict future trends. This free Machine Learning with Python course will give you all the tools you need to get started with supervised and unsupervised learning. This Machine Learning with Python course dives into the basics of machine learning using an approachable, and well-known, programming language. You'll learn about Supervised vs Unsupervised Learning, look into how Statistical Modeling relates to Machine Learning, and do a comparison of each. Look at real-life examples of Machine learning and how it affects society in ways you may not have guessed! Explore many algorithms and models: Popular algorithms: Classification, Regression, Clustering, and Dimensional Reduction. Popular models: Train/Test Split, Root Mean Squared Error, and Random Forests. Get ready to do more learning than your machine! Connect with Big Data University: https://www.facebook.com/bigdatauniversity https://twitter.com/bigdatau https://www.linkedin.com/groups/4060416/profile ABOUT THIS COURSE •This course is free. •It is self-paced. •It can be taken at any time. •It can be audited as many times as you wish. https://bigdatauniversity.com/courses/machine-learning-with-python/A* Graph Search Optimality
🛈⏬Tutorial by Davis Foote This video walks through the proof that A* graph search with a consistent heuristic is optimal, providing intuition for each step at a depth beyond what we have time for in lecture. The video is a bit long, so you may want to watch it sped up and slow down as necessary at parts that trip you up. For your convenience, here are some useful time markers: 0:00-8:54 --- Motivating example 8:54-11:50 --- Defining consistency 11:50-13:18 --- Statement of lemma (The f cost along a path never decreases) 13:18-19:47 --- Proof of lemma 19:47-25:52 --- Proof that A* graph search with a consistent heuristic is optimalWhat's an algorithm? - David J. Malan
🛈⏬View full lesson: http://ed.ted.com/lessons/your-brain-can-solve-algorithms-david-j-malan An algorithm is a mathematical method of solving problems both big and small. Though computers run algorithms constantly, humans can also solve problems with algorithms. David J. Malan explains how algorithms can be used in seemingly simple situations and also complex ones. Lesson by David J. Malan, animation by enjoyanimation.A* Algorithm
🛈⏬Artificial Intelligence by Prof. Deepak Khemani,Department of Computer Science and Engineering,IIT Madras.For more details on NPTEL visit http://nptel.ac.inLecture 3: Informed Search (A*)
🛈⏬CS188 Artificial Intelligence UC Berkeley, Spring 2013 Instructor: Prof. Pieter AbbeelArtificial Intelligence | Tutorial #1 | A Star Algorithm (Solved Problem)
🛈⏬In this video, I'll discuss the steps to solve A* pathfinding algorithm for reaching the goal with the minimum value #RanjiRaj #ArtificialIntelligence #Astar Interact Shaorga Teagaisc # 1: A (Fadhb Réitithe) * Algartam في هذا الفيديو سوف مناقشة الخطوات لحل A * مسار ايجاد خوارزمية للوصول إلى الهدف مع قيمة الحد الأدنى В това видео ще обсъдят стъпките за решаване на A * път намери алгоритъм за постигане на целта, с минимална стойност このビデオでは、最小値で目標に到達するためのA *経路探索アルゴリズムを解決するための手順について説明します 在这个视频中，我将讨论解决A *路径寻找算法的步骤，以达到具有最小值的目标 Dans cette vidéo je vais discuter des étapes pour résoudre A * chemin trouver algorithme pour atteindre l'objectif avec la valeur minimale În acest film voi discuta pașii pentru a rezolva o cale * gasirea algoritm pentru atingerea obiectivului cu o valoare minimă En este video voy a discutir los pasos para resolver A * path encontrar algoritmo para alcanzar la meta con el valor mínimo Neste vídeo, vou discutir as etapas para resolver o algoritmo de localização do caminho A * para alcançar a meta com valor mínimo W tym filmie omówię kroki w celu rozwiązania * ścieżki znajdowanie algorytmu osiągając cel z minimalną wartością En este video voy a discutir los pasos para resolver A * path encontrar algoritmo para alcanzar la meta con el valor mínimo In hoc video ego ad gradus, de * solvere via ad inveniens usque in finem, cum minimum valorem algorithm[Artificial Intelligence] [Tutorial 5] A Star Algorithm
🛈⏬ لو عايز تتعلم ساعد غيرك انه يتعلم متنسوش Like و Share وSubscribe و Endorse my Linkedin Follow me on Facebook : http://on.fb.me/1MqbSFi My Facebook Page : https://www.facebook.com/free.Course.book My Linkedin : https://eg.linkedin.com/in/ahmedmater Don't forgot to Endorse meA* algorithm in artificial intelligence in hindi | a* algorithm in ai | a* algorithm with example
🛈⏬A* algorithm in artificial intelligence in hindi | a* algorithm in ai | a* algorithm with example It is best-known form of Best First search. It avoids expanding paths that are already expensive, but expands most promising paths first. f(n) = g(n) + h(n), where g(n) the cost (so far) to reach the node h(n) estimated cost to get from the node to the goal f(n) estimated total cost of path through n to goal. It is implemented using priority queue by increasing f(n). Follow us on : Facebook : https://www.facebook.com/wellacademy/ Instagram : https://instagram.com/well_academy Twitter : https://twitter.com/well_academy a* algorithm in ai, a* algorithm in artificial intelligence examples, a* algorithm in hindi, a* algorithm in artificial intelligence in english, a* algorithm in artificial intelligence notes, a* algorithm in artificial intelligence tutorial, a* search algorithm in hindi, a* algorithm in artificial intelligence, a* algorithm in artificial intelligence in hindiDeep Learning with TensorFlow - Introduction to TensorFlow
🛈⏬Enroll in the course for free at: https://bigdatauniversity.com/courses/deep-learning-tensorflow/ Deep Learning with TensorFlow Introduction The majority of data in the world is unlabeled and unstructured. Shallow neural networks cannot easily capture relevant structure in, for instance, images, sound, and textual data. Deep networks are capable of discovering hidden structures within this type of data. In this TensorFlow course you'll use Google's library to apply deep learning to different data types in order to solve real world problems. Traditional neural networks rely on shallow nets, composed of one input, one hidden layer and one output layer. Deep-learning networks are distinguished from these ordinary neural networks having more hidden layer, or so-called more depth. These kind of nets are capable of discovering hidden structures within unlabeled and unstructured data (i.e. images, sound, and text), which is the vast majority of data in the world. TensorFlow is one of the best libraries to implement deep learning. TensorFlow is a software library for numerical computation of mathematical expressional, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning. In this TensorFlow course, you will be able to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained. Finally, the course covers different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders. Connect with Big Data University: https://www.facebook.com/bigdatauniversity https://twitter.com/bigdatau https://www.linkedin.com/groups/4060416/profile ABOUT THIS COURSE •This course is free. •It is self-paced. •It can be taken at any time. •It can be audited as many times as you wish. https://bigdatauniversity.com/courses/deep-learning-tensorflow/A* search
🛈⏬Professor Abbeel steps through A* search examples.a* algorithm in artificial intelligence example
🛈⏬a* algorithm in artificial intelligence makes use of a priority queue just like Uniform Cost Search with the element stored being the path from the start state to a particular node, but the priority of an element is not the same. read more from below link https://algorithmicthoughts.wordpress.com/2013/01/04/artificial-intelligence-a-search-algorithm/ ********************************************* WATCH MY ARTIFICIAL INTELLIGENCE ALGORITHM PLAYLIST FROM BELOW LINK ********************************************* https://www.youtube.com/watch?v=7TmhnLHoeL8&list=PLNmFIlsXKJMnaoVHNcwBF07Tu244fn1c1021-Breadth First Search
Unit 2, Topic 23, A-Star Search
🛈⏬Unit 2, Topic 23, A-Star SearchMinimax with Alpha Beta Pruning
A* Search Algorithm | GeeksforGeeks
🛈⏬Complete Code with explanation: http://www.geeksforgeeks.org/a-search-algorithm/ Soundtrack: Nice To You by Vibe Tracks This video is contributed by Rajan GirsaA* Optimality
Decision Tree (CART) - Machine Learning Fun and Easy
🛈⏬Decision Tree (CART) - Machine Learning Fun and Easy ►FREE YOLO GIFT - http://augmentedstartups.info/yolofreegiftsp ►KERAS Course - https://www.udemy.com/machine-learning-fun-and-easy-using-python-and-keras/?couponCode=YOUTUBE_ML Decision tree is a type of supervised learning algorithm (having a pre-defined target variable) that is mostly used in classification problems. A tree has many analogies in real life, and turns out that it has influenced a wide area of machine learning, covering both classification and regression (CART). So a decision tree is a flow-chart-like structure, where each internal node denotes a test on an attribute, each branch represents the outcome of a test, and each leaf (or terminal) node holds a class label. The topmost node in a tree is the root node. ------------------------------------------------------------ Support us on Patreon ►AugmentedStartups.info/Patreon Chat to us on Discord ►AugmentedStartups.info/discord Interact with us on Facebook ►AugmentedStartups.info/Facebook Check my latest work on Instagram ►AugmentedStartups.info/instagram Learn Advanced Tutorials on Udemy ►AugmentedStartups.info/udemy ------------------------------------------------------------ To learn more on Artificial Intelligence, Augmented Reality IoT, Deep Learning FPGAs, Arduinos, PCB Design and Image Processing then check out http://augmentedstartups.info/home Please Like and Subscribe for more videos :)What are Heuristics?
🛈⏬Singapore's curriculum focuses on Mathematical problem solving, hence, there is a great emphasis on the use of heuristics, a problem solving tool. Ms Peggy Foo talks about the examples of heuristics and shows how they can be used to solve Mathematics problems.A* (A Star) Search Algorithm | A* Search Algorithm In Artificial Intelligence[Bangla Tutorial]
🛈⏬A* (A Star) Search Algorithm | A* Search Algorithm In Artificial Intelligence[Bangla Tutorial] ******************************************************************* This tutorial help for basic concept of A* Search Algorithm and it also help gather knowledge of A* Search Algorithm i will provide very basic level concept to advance level concept of Artificial Intelligence if you watching this tutorial i think you will be learn about A* Search Algorithm. If you want to learn more then you must watch this playlist, playlist name Artificial Intelligence if there are any query in A* Search Algorithm in Artificial Intelligence please comment the comment section below, if you want more videos than you subscribe my channel for get update notification, if this video are helping any kind of you than please share my video and like this video and also subscribe my channel Other Videos: What Is Artificial Intelligence: https://goo.gl/YLKkih Breadth First Search:https://goo.gl/LSte2C Depth First Search:https://goo.gl/1rj4yJ Best First Search:https://goo.gl/rn4yvY Bi-directional Search:https://goo.gl/s1NouJ Uniform Cost Serach:https://goo.gl/vH5A9X Heuristic Serach:https://goo.gl/6uMzdr Iterative Deepening Search:https://goo.gl/ofMxr5 Class C subnetting: https://goo.gl/gw2gP1Data Structures: Tries
🛈⏬Learn the basics of tries. This video is a part of HackerRank's Cracking The Coding Interview Tutorial with Gayle Laakmann McDowell. http://www.hackerrank.com/domains/tutorials/cracking-the-coding-interview?utm_source=video&utm_medium=youtube&utm_campaign=ctciA* Algorithm |A* Algorithm example
🛈⏬A* Algorithm |A* Algorithm examplePath Finding Algorithm [A* Algorithm]
🛈⏬I demonstrate how the A* algorithm works, how I implemented it, and show some interesting findings that I discovered along the way! ---------------------------------------------------------------------------------------------------------------- Thanks for watching! Please leave your comments below, I'd love to hear them! I should have my next video up next week! ---------------------------------------------------------------------------------------------------------------- Music: www.bensound.comGraph Data Structure 6. The A* Pathfinding Algorithm
🛈⏬This is the sixth in a series of videos about the graph data structure. It includes a step by step walkthrough of the A* pathfinding algorithm (pronounced A Star) for a weighted, undirected graph. The A* pathfinding algorithm, and its numerous variations, is widely used in applications such as games programming, natural language processing, financial trading systems, town planning and even space exploration. This video demonstrates why the A* pathfinding algorithm may be more appropriate and more efficient than Dijkstra’s shortest path algorithm for many applications, because it is focussed on finding the shortest path between only two particular vertices. The video explains the need for an admissible heuristic, that is, a suitable estimate of the distance between each vertex in the graph and the destination vertex; the example shown here makes use of Manhattan distances for this purpose, calculated on the basis of the grid co-ordinates of each vertex. A description of the pseudocode that leads to an implementation of the A* pathfinding algorithm is also included. When you watch this example, you will see there are occasions when the f values of some open vertices are the same, so the next current vertex is selected from these “for no particular reason”. As pointed out, making one choice or another could have a profound effect on the course of events that follow, but that very much depends on how the algorithm is implemented, and the anatomy of the graph being searched. The search described in this video concludes when the destination vertex is a neighbour of the current vertex - and it shares the lowest f value. Conceivably, another open vertex could have had a lower f value than the destination at this stage, so the search for a shorter path would continue. Again, exactly how the algorithm finishes is a matter of implementation. If you investigate this subject further, you will discover there are lots of ways the algorithm can be adapted. Using a priority queue for the open vertices is one way, pre-processing the graph data to calculate the h values is another. The basic A* pathfinding algorithm descried here is really just a starting point.Total Unique Ways To Make Change - Dynamic Programming (-Coin Change 2- on LeetCode)
🛈⏬Come Visit Us: https://backtobackswe.com Question: You are given coins of different denominations and a total amount of money. Write a function to compute the number of combinations that make up that amount. You may assume that you have an infinite number of each kind of coin. The code: https://github.com/bephrem1/backtobackswe/blob/master/Dynamic%20Programming%2C%20Recursion%2C%20%26%20Backtracking/changeMakingProblem2.java Examples: 1 Input: amount = 5, coins = [1, 2, 5] Output: 4 5=5 5=2+2+1 5=2+1+1+1 5=1+1+1+1+1 2 Input: amount = 3, coins = [2] Output: 0 Can't make change for this amount given the coins we have. This problem is very similar to the 0 / 1 knapsack problem. We will use a bottom up dynamic programming approach to build to our final answer. We will consider the total ways to make change with just the 1st coin, with just the 1st and 2nd coin, with just the 1st, 2nd, and 3rd, coin, and so on... Complexities A is the amount to make change for. n is the total denominations avaliable to us. Time: O( A * n ) For each denomination we will be solving A subproblems. So for each of the n we will be doing A work, hence multiplication. Space: O( A * n ) Hold the answer to all subproblems. Note: We can do this in just O( A ) space but we did it this way for simplicity ++++++++++++++++++++++++++++++++++++++++++++++++++ HackerRank: https://www.youtube.com/channel/UCOf7UPMHBjAavgD0Qw5q5ww Tuschar Roy: https://www.youtube.com/user/tusharroy2525 GeeksForGeeks: https://www.youtube.com/channel/UC0RhatS1pyxInC00YKjjBqQ Jarvis Johnson: https://www.youtube.com/user/VSympathyV Success In Tech: https://www.youtube.com/channel/UC-vYrOAmtrx9sBzJAf3x_xw ++++++++++++++++++++++++++++++++++++++++++++++++++ This question on Leetcode: https://leetcode.com/problems/coin-change-2Dijkstra's Algorithm (Decision Maths 1)
🛈⏬Using Dijkstra's Algorithm to find the shortest path between 2 points in a network www.hegartymaths.com http://www.hegartymaths.com/Constraint satisfaction problems
🛈⏬Main algorithms to solve discrete constraint satisfaction problems. Chapter 5 of Artificial Intelligence, a modern approach by Russel and Norvig.Path Planning - A* (A-Star)
🛈⏬A tricky one to do a video about this, but here is an tutorial implementation of the A* path finding algorithm, programmed in C++, running at the command prompt. Lol, forgot the source: https://github.com/OneLoneCoder/videos/blob/master/OneLoneCoder_PathFinding_AStar.cpp Blog: www.onelonecoder.comBackpropagation in 5 Minutes (tutorial)
🛈⏬Let's discuss the math behind back-propagation. We'll go over the 3 terms from Calculus you need to understand it (derivatives, partial derivatives, and the chain rule and implement it programmatically. Code for this video: https://github.com/llSourcell/how_to_do_math_for_deep_learning Please Subscribe! And like. And comment. That's what keeps me going. I've used this code in a previous video. I had to keep the code as simple as possible in order to add on these mathematical explanations and keep it at around 5 minutes. More Learning resources: https://mihaiv.wordpress.com/2010/02/08/backpropagation-algorithm/ http://outlace.com/Computational-Graph/ http://briandolhansky.com/blog/2013/9/27/artificial-neural-networks-backpropagation-part-4 https://jeremykun.com/2012/12/09/neural-networks-and-backpropagation/ https://mattmazur.com/2015/03/17/a-step-by-step-backpropagation-example/ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Forgot to add my patron shoutout at the end so special thanks to Patrons Tim Jiang, HG Oh, Hoang, Advait Shinde, Vijay Daniel & Umesh Rangasamy Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w